Diagnostic technologies directed towards detecting viral or bacterial infections, or other ailments, within a biological sample generally do not have the sensitivity to directly detect the presence of infectious agents such as a bacteria, virus, or diseased tissue (e.g. cancer) before an immune response occurs. Thus, most diagnostic technologies detect such infections or ailments through detection of antibodies created by a patient's immune system in response to the particular condition. For example, these antibody detection techniques are currently not capable of detecting many diseases within the first month of infection (e.g. Lyme disease). There are laboratory scale analytical and sample treatment techniques capable of detecting markers at an early stage of infection. However, these laboratory techniques require time, expertise and material that prevent common clinical use. One of these laboratory scale sensors is based on direct detection using carbon nanotube devices. Such sensors have been developed in academic labs worldwide. A related material, Graphene, has seen less academic development, but is widely understood to have similar potential use. However, these specialized nanoelectronics lab technologies have yet to be converted into a practical diagnostic systems or methods.
Generally, biological sample analysis to determine the presence of antibodies may be performed on blood or urine samples. Current blood diagnostic systems rely on technologies including enzyme-linked immunoassay (ELISA), gel electrophoresis and blood culture. These are all proven, mature technologies. All three of these tests require significant time to run, from several hours to several days.
ELISA and gel electrophoresis tests generally measure an immune system response to a disease (e.g. the presence of antibodies), rather than presence of the disease itself. Most diagnostic tests, including ELISA and gel electrophoresis tests, require detection of a reporter molecule or molecular label. In these tests a reporter or amplifier molecule is required to generate a measurable signal.
All of these tests require either significant expertise or very expensive automation equipment to run. This is partly due to the multiple steps and specialized reagents required. For example, ELISA tests are particular complicated. ELISA tests include coating a measurement well or surface with a copy of a chemical marker created by an infectious agent known as an antigen, incubating a biological sample (e.g. blood, serum, urine, or cerebrospinal fluid), and exposing the measurement well to the biological sample to allow the antibody, if present, to bind to the antigen. The binding process is subject to thermodynamic laws of probability and is not perfect such that some antibodies will bind incorrectly or fail to bind where they should. The ELISA test further includes washing the patient sample from the well, adding a solution with a reporting antibody intended to bind to antibodies bound to the well wall, rinsing the well a second time, and adding a reporting dye to the intended to change colors in the presence of reporting dye. These steps are also subject to variances in binding efficiency and accuracy.
Gel electrophoresis tests are also complicated. In many cases, ELISA is generally preferred for cost and difficulty. Not all infectious agents can be detected by using a blood culture, for example infection with Borelia burgdoferi is not generally identified via blood culture. The complexity of these tests makes them extremely operator dependent, creating the possibility for variance in test result accuracy depending on the experience and skill of the operator. Automation could improve accuracy and decrease testing variance, but no such automated solutions are readily available.
Another biological sample analysis technique is based on the polymerase chain reaction (PCR), which clones targeted small fragments of DNA. This is a highly sensitivity technique, but also requires either significant expertise or very expensive automated equipment to run properly, and requires several hours for each test.
All of these currently available tests are costly, highly operator dependent, and lack the sensitivity specificity to accurately and reliably detect many diseases, particularly in the disease's early states (e.g. Lyme disease).